Development and evaluation of a novel robotic system for search and rescue

Search and Rescue robotics is a relatively new field of research, which is growing rapidly as new technologies emerge. However, the robots that are usually applied to the field are generally small and have limited functionality, and almost all of them rely on direct control from a local operator. In this paper, a novel wheeled Search and Rescue robot is proposed which considers new methods of controlling the robot, including using a wireless “tether” in place of a conventional physical one. A prototype is then built which acts as a proof of concept of the robot design and wireless control. The prototype robot is then evaluated to prove its mobility, wireless control and multi-hop networking. The experimental results demonstrate the effectiveness of the proposed design incorporating the rocker-bogie suspension system and the multi-hop method of “wireless tethering”

Training a terrain traversability classifier for a planetary rover through simulation

A classifier training methodology is presented for Kapvik, a micro-rover prototype. A simulated light detection and ranging scan is divided into a grid, with each cell having a variety of characteristics (such as number of points, point variance and mean height) which act as inputs to classification algorithms. The training step avoids the need for time-consuming and error-prone manual classification through the use of a simulation that provides training inputs and target outputs. This simulation generates various terrains that could be encountered by a planetary rover, including untraversable ones, in a random fashion. A sensor model for a three-dimensional light detection and ranging is used with ray tracing to generate realistic noisy three-dimensional point clouds where all points that belong to untraversable terrain are labelled explicitly. A neural network classifier and its training algorithm are presented, and the results of its output as well as other popular classifiers show high accuracy on test data sets after training. The network is then tested on outdoor data to confirm it can accurately classify real-world light detection and ranging data. The results show the network is able to identify terrain correctly, falsely classifying just 4.74% of untraversable terrain

Terrain response estimation using an instrumented rocker-bogie mobility system

This paper presents a procedure to model the drawbar pull and resistive torque of an unknown terrain as a function of normal load and slip using on-board rover instruments. Kapvik , which is a planetary micro-rover prototype with a rocker-bogie mobility system, is simulated in two dimensions. A suite of sensors is used to take relevant measurements; in addition to typical rover measurements, forces above the wheel hubs and rover forward velocity are sensed. An estimator determines the drawbar pull, resistive torque, normal load, and slip of the rover. The collected data are used to create a polynomial fit model that closely resembles the real terrain response